Diabetes Technology Society

The postprandial glycemic response (PPGR) is associated with diabetes and cardiovascular disease and is highly individualized. The PPGR is affected by both physiological and behavioral factors. Attention to the PPGR has dramatically increased recently with the widespread use of continuous glucose monitors. It is expected that individualized control of PPGRs will be important in the prevention of diabetes and its associated complications. In this article, we discuss six modifiable factors associated with the PPGRs, including (1) the glucoregulatory hormones, (2) gastric emptying, (3) salivary or pancreatic amylase, (4) diet, (5) physical exercise, and (6) sleep and circadian rhythm. Modifying these factors may allow for personalized intervention strategies to control the PPGR-to reduce the risk for cardiovascular disease in individuals with varying degrees of glycemia.

Prior studies have not identified if continuous glucose monitoring (CGM) metrics at a critical gestational age window can discriminate risk of adverse pregnancy outcomes. We evaluated late second- and third-trimester CGM metrics by gestational age associated with pregnancy outcomes in gravidas with type 1 diabetes (T1DM). Dexcom G6 CGM data from a retrospective cohort of singleton gestations with T1DM (2018-2022) at an academic medical center were analyzed. Time in, above, and below range 63 to 140 mg/dL (TIR, TAR, TBR), glycemic variability, and mean glucose concentration were computed in two-week CGM intervals from 240 to 396 weeksdays. Adverse pregnancy outcomes were hypertensive disorders of pregnancy (HDP), large-for-gestational age (LGA), and neonatal hypoglycemia. Linear mixed-effects models were fitted on CGM metrics computed from two-week CGM intervals, with gestational age, adverse pregnancy outcomes (i.e. presence/absence of HDP, LGA, and/or neonatal hypoglycemia), and their interaction as fixed effects. In 87 gravidas with preconception median hemoglobin A1c 6.5% (IQR 6.0, 7.1) and maternal body mass index 24.8 kg/m2 (IQR 21.9, 27.1), 71% had at least one adverse pregnancy outcome. Between weeks 240 and 376, gravidas with HDP had higher TAR and mean glucose and lower TIR (P < .05). Gravidas with LGA had lower TBR between weeks 240 and 356. TIR, TAR, and mean glucose evolution differed by HDP status, with greatest divergence between groups at 280 to 296 weeks' gestation (P ≤ .001). CGM metrics in the late second to early third trimester, a period of peak insulin resistance, may help to distinguish risk of HDP and LGA in gravidas with T1DM.

The advanced glycation end products (AGEs) Webinar was co-hosted by Diabetes Technology Society and Kitalys Institute on August 8, 2024, with the goal of reviewing progress made in the measurement and use of AGEs in clinical practice. Meeting topics included (1) AGEs as predictors of diabetic nephropathy (DKD), (2) hemoglobin glycation index (HGI) and the glycation gap (GG), (3) formation and structure of AGEs, (4) AGEs as a risk factor of cardiovascular disease (CVD), and (5) approaches to limit or prevent AGE formation.

The timing, intensity, and duration of postprandial exercise are important factors that reduce glucose excursions. When exercise is of moderate intensity, performed between 25 and 55 minutes after a meal, it results in greater attenuation of glucose. However, the potential glucose reduction for shorter-duration, non-exercise activity thermogenesis (NEAT) (such as activities of daily living) may also be beneficial, particularly in cases where exercise is neither feasible nor prudent. Therefore, we designed a system to capture blood glucose and activity intensity through internet of medical things devices and modeled the impact of the timing and duration of NEAT on peak glucose. This work designed a linear mixed effects model to evaluate the impact of NEAT on peak, postprandial glucose in a study of data captured on varied participants with or without diabetes. We found at least 25 minutes of NEAT starting 30 minutes after the meal most effectively reduced peak post-prandial glucose.Clinical Relevance— This work establishes the impact of NEAT on reducing post-prandial peak glucose in free-living environments as another method of controlling glucose surges

A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data. We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation. The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals. The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Medical products are used increasingly by patients with diabetes as they make diabetes therapy more safe and efficient; subsequently such products are produced and used millions of times each day. This in turn means that the products themselves and the packaging adds up to a huge amount of waste, mainly plastic waste. Not only patients are well aware of this and start to complain about this, in view of the climate change the political pressure to change the situation is high and will increase further. A better balance between performance of the products and their environmental impact has to be found; however, diabetes technology and waste is a complex story with many different aspects.